The characterization of a radio signal in the presence of noise is a classic radio problem. Commonly called “co-channel” or “adjacent channel” interference, spurious signals are considered part of the radio noise that a receiver must deal with in the course of normal operation.
As the use of wireless communications has increased from traditional radio and television broadcasts to two-way terrestrial and satellite wireless communications, the value of radio transmissions has increased. And as the value of radio transmissions has increased, the problem of intentional interference, such as denial of service attacks, have also increased.
Detection of an interfering radio signal and characterization of the interfering signal is well known in the art. Geolocation techniques have been created suitable to wide area deployment, mostly under the auspices of the United States (US) Federal Communications Commission (FCC) Enhanced 9-1-1 mandate. For example, several experiments were conducted during several months of 1995 and 1996 in the cities of Philadelphia and Baltimore to verify the system's ability to mitigate multipath in large urban environments. In 1996, TruePosition constructed the first commercial system in Houston Tex. that was used to test the technology's effectiveness in that area and its ability to interface directly with E9-1-1 systems. In 1997, the location system was tested in a 350 square mile area in the State of New Jersey and was used to locate real 9-1-1 calls from real people in trouble.
The following is an overview of network-based geo-location techniques applicable to locating generic interfering radio signals over a wide area.
Geolocation Techniques
Geolocation is the process of determining the source of a radio frequency (RF) signal by exploiting the characteristics of radio wave propagation. As radio waves propagate from their point of origin, the waves emanate as spherical waves in all directions. The waves exhibit a time delay because they travel at a fixed speed and with an apparent reduction in power because of spherical spreading. Thus, at a point of reception that is fixed with respect to a fixed point of origin, an RF signal appears to originate from a specific direction, exhibit a time delay that is proportional to the distance between the point of origin and point of reception, and reduced in power by an amount proportional to the distance between the point of origin and point of reception.
Geolocation techniques that exploit time delays are known as Time-of-Arrival (TOA) and Time-Difference-of-Arrival (TDOA) techniques. Geolocation techniques that exploit the change in power of radio wave characteristics are know as Power-of-Arrival (POA) and Power-Difference-of-Arrival (PDOA) techniques. Angle-of-Arrival (AoA) geolocation techniques measure the direction from which a source of RF appears to originate. Radio waves also experience an apparent change in frequency as a result of the Doppler effect when the source is moving or the sensor receiving the source is moving. The amount of frequency shift is dependent upon the center frequency of the source as well as the relative velocity between the source and receiving sensor. Geolocation techniques that exploit this characteristic of RF signal propagation are known as Frequency-Difference-of-Arrival (FDOA) techniques.
Each geolocation technique provides different levels of performance in terms of location accuracy and impose different requirements on the sensors (i.e. software defined radios (SDRs)) in a Wide Area Sensor Network (WASN). A key benefit of the WASN is a sensor platform that is calibrated in power and synchronized in time and frequency to permit the exploitation of all of the characteristics of radio wave propagation to determine the origins of RF signals. The multichannel RF to IF stage of the SDR permits the SDR to utilize a direction finding antenna array to determine the AoA of incident RF energy. Each approach can be utilized separately or combined with other techniques, i.e. hybrid geolocation.
Time-of-Arrival (TOA) Based Geolocation:
Network-based TOA location uses the relative time of arrival of a radio broadcast at the network-based receivers. This technique requires that the distance between individual receiver sites (SDRs) and any differences in individual receiver timing be known (cabling delays, differences in SDR designs or radio group delay). The radio signal time-of-arrival can then be normalized at the receiver site, leaving only the time-of-flight between the device and each receiver. Since radio signals travel with a known velocity, the distance can be calculated from derived, normalized time-of-arrivals at the receivers. Time-of-arrival data collected from three or more receivers may be used to resolve the precise position.
Time-Difference-of-Arrival (TDOA) Based Geolocation:
TDOA is the most accurate and useful time-based geolocation technique for emitters that are not cooperative. TDOA requires close time synchronization between the SDRs in the WASN. When two sensors receive a RF signal simultaneously and the time delay between these two received signals is determined, it is well known that a hyperbola, with the two sensors at its foci, describes the potential locations of the originating signal. Adding a third sensor, again time synchronized with the other two and receiving the same signal simultaneously, provides another hyperbola. The intersection of these two hyperbola reveals a unique location as the source of the RF energy. Adding even more sensors yields a greater location accuracy with an over determined solution. TDOA location accuracy depends upon the bandwidth of the signal being located as well as a number of other factors such as integration time and signal-to-noise ratio. Additional detail on using TDOA to locate transmitters (e.g., mobile phones) can be found in commonly assigned U.S. Pat. No. 5,327,144—“Cellular telephone location system” and U.S. Pat. No. 6,047,192—“Robust, efficient, localization system.”
Additional details on using TDOA hybrids to locate transmitters (e.g., mobile phones) can be found in commonly assigned U.S. Pat. No. 6,108,555—“Enhanced time difference localization system” and U.S. Pat. No. 6,119,013—“Enhanced time-difference localization system.”
Angle-of-Arrival (AoA) Based Geolocation:
The SDRs of the WASN possess multichannel phase and frequency coherent circuitry, permitting the use of phase interferometric antenna arrays to be used to determine the angle-of-arrival (AoA) of RF signals. In effect, the AoA points to the direction from which the RF energy originated. A unique location can be estimated by determining the AoA at two or more geometrically separated sites. The unique location is represented by the intersection of the two or more lines of bearing. AoA does not require fine time or frequency synchronization between the sites and providing AoA information to the system controller/central processor. Furthermore, AoA accuracy is not dependent upon the bandwidth of the emitter as with UTDOA, providing the capability to geolocate on narrowband signals. Additional detail on using AoA to locate transmitters (mobile phones) can be found in commonly assigned U.S. Pat. No. 4,728,959—“Direction finding localization system.” Additional detail on using AoA/TDOA hybrids to locate transmitters (mobile phones) can be found in commonly assigned U.S. Pat. No. 6,119,013—“Enhanced time-difference localization system.”
Power-Of-Arrival (POA) and Power-Difference-Of-Arrival (PDOA) Based Geolocation:
An approximate location of an emitter may be determined by measuring its power at various locations. Measurement can be performed simultaneously with multiple sensors or in a time multiplexed fashion by moving a single sensor to several locations for emitters that transmit a constant power for a significant length of time. Power based geolocation techniques do not have as stringent time and frequency synchronization requirements as the other geolocation techniques discussed above. However, fast fading and shadow fading may limit the accuracy of this method.
Since the power of a radio signal decreases with distance as a result of attenuation of radio waves by the atmosphere and the combined effects of free space loss, plane earth loss, and diffraction losses, an estimate of the distance can be determined from the received signal. In simplest terms, as the distance between transmitter and receiver increases, the radiated radio energy is modeled as if spread over the surface of a sphere. This spherical model means that the radio power at the receiver is decreased by at least the square of the distance.
POA
Power of arrival is a proximity measurement used between a single network node (the SDR) and transmitter. POA location uses the relative power of arrival of a radio broadcast at the network-based SDRs.
Using signal propagation modeling and historical calibration data, the radio signal power-of-arrival can be normalized at the receiver site, leaving only the path-loss between the device and each receiver. Power-of-arrival data collected from three or more receivers can be used to resolve an approximate position.
PDOA
PDOA uses the absolute differences in received radio power at multiple receivers to compute a position. PDOA location techniques require that receiver locations be known a priori. Signal propagation modeling and/or historical calibration data can be used to improve the location estimate. Power data collected from three of more receivers using a common time-base can be used to resolve an approximate position.
Frequency-Difference-Of-Arrival (FDOA)
Using FDOA to determine an approximate location of an emitter is performed by measuring the signal's frequency at various locations. Measurement is performed simultaneously with multiple sensors or in a time multiplexed fashion by moving a single sensor to several locations for emitters that transmit for a significant length of time.
Frequency-Difference-of-Arrival uses measurement of signal frequency offsets as received at multiple receivers. Due to the differing Doppler-induced frequency offsets, FDOA provides speed and heading of moving transmitters. To use FDOA for location estimation, either or both the transmitter or receiver(s) must be in motion.
Since both the FDOA and TDOA techniques require a precise timing source (common clock and a common frequency reference), both techniques can be used simultaneously for localization as described in commonly assigned U.S. Pat. No. 6,876,859—“Method for estimating TDOA and FDOA in a wireless location system.”
Hybrid Geolocation Techniques:
All the described location techniques can be used for the localization of an emitter by using techniques such as a Weighted Least Squares or Constrained Least Squares algorithm which allows the additive probability of each location technique to render a best location estimate for the technique or mix of techniques used.
The great dependence of a modern society upon wireless systems creates vulnerabilities to disruption of the wireless systems. Wireless equipment is relatively unprotected to disruption by jamming and interference whether inadvertent or intentional. A system that is capable of being deployed over a wide area that detects, classifies and locates wireless signals would be useful for monitoring the airwaves for interference to critical wireless signals. It would be advantageous to use one or more of the above geolocation techniques in a Wide Area Sensor Network to identify and locate intentional and unintentional sources of interference over a geographic area of interest.
In addition, another problem addressed by the solutions described herein relates to the need for improved methods and systems for determining an accurate position of one or more location sensors of a WLS. In particular, geolocation with TOA or TDOA techniques with a network of sensors requires that the location of the sensors (also known as Positioning Determining Entities (PDEs), Signal Collection Systems (SCSs) or Location Measurement Units (LMUs)) be known and that the sensors be tightly synchronized with each other in time. Frequency-Difference-of-Arrival (FDOA) geolocation techniques with a network of sensors require the sensor locations to be known and that the sensors be tightly synchronized with each other in frequency. Utilizing GNSS receivers in the static sensors provides a convenient way to determine the locations of the sensors as well as to achieve a high level of time and frequency synchronization performance. However, GNSS receivers can only provide this level of location and synchronization performance when they have an unobstructed view of the sky. In many operational deployment scenarios, a clear view of the sky, or even a view of a significant fraction of the sky, is not feasible. Therefore, it would be advantageous to include a hybrid or fallback technique into the sensor platform for determining the sensor's position as well as synchronizing to the other sensors in the WLS in time and frequency, in effect, providing diversity for synchronizing the sensors and determining their location.